Abstract
This paper deals with the study of robustness in genetic algorithms from the viewpoint of population diversity when dealing with a complex combinatorial optimization problem. In this case, robustness of algorithms for the job shop scheduling problem in the presence of processing time and number of job perturbations is studied. Three different algorithms are compared: a standard genetic algorithm and two selection level diversity control methods. Definitions of robustness and diversity are presented in order to build a framework for the study of their relations. It is concluded in this research that the key to obtaining a robust design is neither accuracy nor diversity but an exigent combination of both.
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